We analyze numerically the effect of a slight inclination in the lowest part of the snaking branches of convectons that are present in negative separation ratio binary mixtures in two-dimensional elongated rectangular cells. The exploration reveals the existence of novel stationary localized solutions with striking spatial features different from those of convectons. The numerical continuation of these solutions with respect to the inclination of the cell unveils the existence of even further families of localized structures that can organize in closed branches. A variety of localized solutions coexist for the same heating and inclination, depicting a highly complex scenario for solutions in the lowest part of the snaking diagrams for moderate to high heating. The different localized solutions obtained in the horizontal cell are discussed in detail.

We establish multicomponent $1+$ injection into a charge breeder electron cyclotron resonance ion source and an associated computational procedure as a noninvasive probe of the electron density $n_e$, average electron energy $\langle E_e\rangle$, and the characteristic times of ionization, charge exchange, and ion confinement of stochastically heated, highly charged plasma. Multicomponent injection allows refining the $n_e$, $\langle E_e\rangle$ ranges, reducing experimental uncertainty. Na/K injection is presented as a demonstration. The $\langle E_e\rangle$ and $n_e$ of a hydrogen discharge are found to be ${600}_{-300}^{+600}\mathrm{eV}$ and $8_{-3}^{+8}\times {10}^{11}{\mathrm{cm}}^{-3}$, respectively. The ionization, charge exchange, and confinement times of high charge state alkali ions are on the order of 1 ms–10 ms.

The Achlioptas process, a percolation algorithm on random network, shows a rapid second-order phase transition referred to as explosive percolation. To obtain the transition point and critical exponent $\beta$ for percolations on a random network, especially for bond percolations, we propose a new scaling analysis that is independent of the system size. The transition point and critical exponent $\beta$ are estimated for the product-rule (PR) and da Costa-Dorogovtsev-Goltsev-Mendes (dCDGM) ($m=2$) models of the Achlioptas process, as well as for the Erdős-Rényi (ER) model, which is a classical model in which the analytic values are known. The validity of the scaling analysis is confirmed, especially for the transition point. The estimations of $\beta$ are also consistent with previously reported values for the ER and dCDGM(2) models, whereas the $\beta$ estimation for the PR model deviates somewhat. By introducing a parameter representing the maximum cluster size, we develop an extrapolation scheme for the critical exponent $\beta$ from the simulation just at the transition point in order to obtain a more accurate value. The estimated value of $\beta$ is improved compared with that obtained by the scaling analysis for the ER model and is also consistent with the $\beta$ value obtained for the dCDGM(2) model, whereas its deviation from the previously reported value is larger for the PR model. We discuss the accuracy of the present estimations and draw conclusions about their reliability.

Nonlocally coupled oscillators with a phase lag self-organize into various patterns, such as global synchronization, the twisted state, and the chimera state. In this paper, we consider nonlocally coupled oscillators that move on a ring by randomly exchanging their positions with the neighbors and investigate the combined effects of phase lag and mobility on the collective phase dynamics. Spanning the whole range of phase lag and mobility, we show that mobility promotes synchronization for an attractive coupling, whereas it destroys coherence for a repulsive coupling. The transition behaviors are discussed in terms of the timescales of synchronization and diffusion of the oscillators. We also find a novel spatiotemporal pattern at the border between coherent and incoherent states.

Knotted proteins, when forced through the pores, can get stuck if the knots in their backbone tighten under force. Alternatively, the knot can slide off the chain, making translocation possible. We construct a simple energy landscape model of this process with a time-periodic potential that mimics the action of a molecular motor. We calculate the translocation time as a function of the period of the pulling force, discuss the asymptotic limits and biological relevance of the results.

Dry-land ecosystems have become a matter of grave concern, due to the growing threat of land degradation and bioproductivity loss. Self-organized vegetation patterns are a remarkable characteristic of these ecosystems; apart from being visually captivating, patterns modulate the system response to increasing environmental stress. Empirical studies hinted that herbivory is one the key regulatory mechanisms behind pattern formation and overall ecosystem functioning. However, most of the mathematical models have taken a mean-field strategy to grazing; foraging has been considered to be independent of spatial distribution of vegetation. To this end, an extended version of the celebrated plant-water model due to Klausmeier has been taken as the base here. To encompass the effect of heterogeneous vegetation distribution on foraging intensity and subsequent impact on entire ecosystem, grazing is considered here to depend on spatially weighted average vegetation density instead of density at a particular point. Moreover, varying influence of vegetation at any location over gazing elsewhere is incorporated by choosing a suitable averaging function. A comprehensive analysis demonstrates that inclusion of spatial nonlocality alters the understanding of system dynamics significantly. The grazing ecosystem is found to be more resilient to increasing aridity than it was anticipated to be in earlier studies on nonlocal grazing. The system response to rising environmental pressure is also observed to vary depending on the grazer. Obtained results also suggest the possibility of multistability due to the history dependence of the system response. Overall, this work indicates that the spatial heterogeneity in grazing intensity has a decisive role to play in the functioning of water-limited ecosystems.

We show that dislocations in active two-dimensional (2D) smectic liquid crystals with underlying rotational symmetry are always unbound in the presence of noise, meaning the active smectic phase does not exist for nonzero noise in $d=2$. The active smectic phase can, like equilibrium smectics in 2D, be stabilized by applying rotational symmetry-breaking fields; however, even in the presence of such fields, active smectics are still much less stable against noise than equilibrium ones, when the symmetry-breaking field(s) are weak.

We report experimental evidence of a Gardner-like crossover from variable to persistent force contacts in a two-dimensional bidisperse granular crystal by analyzing the variability of both particle positions and force networks formed under uniaxial compression. Starting from densities just above the freezing transition and for variable amounts of additional compression, we compare configurations to both their own initial state and to an ensemble of equivalent reinitialized states. This protocol shows that force contacts are largely undetermined when the density is below a Gardner-like crossover, after which they gradually transition to being persistent, being fully so only above the jamming point. We associate the disorder that underlies this effect with the size of the microscopic asperities of the photoelastic disks used, by analogy to other mechanisms that have been previously predicted theoretically.

Particle image velocimetry has been applied to measure particle velocities on the free surface of a bed of particles within a rotating cylinder during avalanching. The particle velocities were used to examine the validity of existing avalanche models and to propose an alternative model. The movement of particles depends on their location on the surface of the bed: Particles located near the center of the bed travel the farthest, while the distance traveled decreases at an increasing rate for particles located farther from the center. The start of an avalanche can be determined to a single initiation point that can be located on the bottom half of the bed; the avalanche quickly propagates through the entire free surface with 90% of the surface in motion within 257 ms (approximately 20% of the total duration of an avalanche). The experimental insight is used to formulate a geometric model, in which three equal-sized sections flow down the bed surface during an avalanch. The predictions of the model are validated by experimental mixing measurements.

We consider a minimal spin model for Ising transitions in an isotropic elastic medium in the zero thermal expansion (ZTE) limit. We set up the elastic theory for this system. We use this theory to identify and study the nature of the fluctuations in the system near the second order phase transitions at $T_c$ in the ZTE limit given by $d{T}_c/dV=0$, where $V$ is the system volume, and explore anomalous elasticity. Allowing for the local strain to couple asymmetrically or selectively with the states of the order parameter, we uncover the dramatic effects of these couplings on the fluctuations of the local displacements near $T_c$, and also on the nature of the phase transition itself. Near second-order phase transitions and with weak asymmetry in the order parameter–strain couplings, the variance of the displacement fluctuations in two dimensions scale with the system size $L$ in a universal fashion as ${[ln(L/a_0)]}^{2/3}$; $a_0$ is a small-scale cutoff. Likewise, the correlation functions of the difference of the local displacements at two different points separated by $r$ scale as ${[ln(r/a_0)]}^{2/3}$ for large $r$. For stronger selectivity above a finite threshold, this variance diverge as $L$ exceeds beyond a (nonuniversal) size, determined by the model parameters, signaling a transition to a phase with only short-range order or the loss of the positional order of the elastic medium. At dimensions higher than two, for sufficiently weak selectivity, the variance of the displacement fluctuations is $L$-independent corresponding to long-range order. However, if the selectivity parameters rise beyond a dimension-dependent threshold value, then again the positional order is lost with a concomitant transition to a phase with short-range order. Large values of the order parameter–strain couplings can turn the phase transition into a first order as well. Our theory establishes a one-to-one correspondence between the order of phase transitions and anomalous elasticity near the transitions. Our theory should be a useful guide to possible synthesis of appropriate ZTE materials.

How to give a statistical description of the thermodynamics in quantum systems is an open fundamental question. Concerning the work, the presence of initial quantum coherence in the energy basis can give rise to a quasiprobability of work, which can take negative values. Our aim is to identify the most general quasiprobability of work satisfying some fundamental conditions. By doing so, we introduce a general notion of quasiprobability in analogy to Gleason's theorem. Then, we use these quasiprobabilities to define the quasiprobability of work, and finally we discuss the contextuality of the protocol.

We study the effects of stochastic birth and death processes on the structural phases of systems of active and passive Brownian particles subject to volume exclusion. The total number of particles in the system is a fluctuating quantity, determined by the birth and death parameters and on the activity of the particles. As the birth and death parameters are varied, we find liquid, hexatic, and solid phases. For passive particles, these phases are found to be spatially homogeneous. For active particles, motility-induced phase separation (coexisting hexatic and liquid phases) occurs for large activity and sufficiently small birth rates. We also observe a reentrant transition to the hexatic phase when the birth rate is increased. This results from a balance of an increasing number of particles filling the system, and a larger number of defects resulting from the birth and death dynamics.

Our goal in this article is to elucidate the rapport of work and information in the context of a minimal quantum-mechanical setup: a converter of heat input to work output, the input consisting of a single oscillator mode prepared in a hot thermal state along with a few much colder oscillator modes. The core issues we consider, taking account of the quantum nature of the setup, are as follows: (i) How and to what extent can information act as a work resource or, conversely, be redundant for work extraction? (ii) What is the optimal way of extracting work via information acquired by measurements? (iii) What is the bearing of information on the efficiency-power tradeoff achievable in such setups? We compare the efficiency of work extraction and the limitations of power in our minimal setup by different, generic, measurement strategies of the hot and cold modes. For each strategy, the rapport of work and information extraction is found and the cost of information erasure is allowed for. The possibilities of work extraction without information acquisition, via nonselective measurements, are also analyzed. Overall, we present, by generalizing a method based on optimized homodyning that we have recently proposed, the following insight: extraction of work by observation and feedforward that only measures a small fraction of the input is clearly advantageous to the conceivable alternatives. Our results may become the basis of a practical strategy of converting thermal noise to useful work in optical setups, such as coherent amplifiers of thermal light, as well as in their optomechanical and photovoltaic counterparts.

The surface entropic exponents of half-space lattice stars grafted at their central nodes in a hard wall are estimated numerically using the PERM algorithm. In the square half-lattice the exact values of the exponents are verified, including Barber's scaling relation and a generalization for 2-stars with one and two surface loops respectively. This is the relation ${\gamma }_{211}=2{\gamma }_{21}-{\gamma }_{20},$ where ${\gamma }_{21}$ and ${\gamma }_{211}$ are the surface entropic exponents of a grafted 2-star with one and two surface loops, respectively, and ${\gamma }_{20}$ is the surface entropic exponent with no surface loops. This relation is also tested in the cubic half-lattice where surface entropic exponents are estimated up to 5-stars, including many with one or more surface loops. Barber's scaling relation and the relation ${\gamma }_{3111}={\gamma }_{30}-3{\gamma }_{31}+3{\gamma }_{311}$ are also tested, where the exponents $\{{\gamma }_{31},{\gamma }_{311},{\gamma }_{3111}\}$ are of grafted 3-stars with one, two, or three surface loops, respectively, and ${\gamma }_{30}$ is the surface exponent of grafted 3-stars.

We consider an overdamped run-and-tumble particle in two dimensions, with self-propulsion in an orientation that stochastically rotates by ${90}^{\circ }$ at a constant rate, clockwise or counterclockwise with equal probabilities. In addition, the particle is confined by an external harmonic potential of stiffness $\mu$, and possibly diffuses. We find the exact time-dependent distribution $P(x,y,t)$ of the particle's position, and in particular, the steady-state distribution $P_{\text{st}}(x,y)$ that is reached in the long-time limit. We also find $P(x,y,t)$ for a “free” particle, $\mu =0$. We achieve this by showing that, under a proper change of coordinates, the problem decomposes into two statistically independent one-dimensional problems, whose exact solution has recently been obtained. We then extend these results in several directions, to two such run-and-tumble particles with a harmonic interaction, to analogous systems of dimension three or higher, and by allowing stochastic resetting.

In this paper, a geometrical and thermodynamical analysis of the global properties of the potential energy landscape of a minimalistic model of a polypeptide is presented. The global geometry of the potential energy landscape is supposed to contain relevant information about the properties of a given sequence of amino acids, that is, to discriminate between a random heteropolymer and a protein. By considering the SH3 and PYP protein-sequences and their randomized versions it turns out that, in addition to the standard signatures of the folding transition—discriminating between protein sequences of amino acids and random heteropolymer sequences—also peculiar geometric signatures of the equipotential hypersurfaces in configuration space can discriminate between proteins and random heteropolymers. Interestingly, these geometric signatures are the “shadows” of deeper topological changes that take place in correspondence with the protein folding transition. The protein folding transition takes place in systems with a small number of degrees of freedom (very far from the Avogadro number) and in the absence of a symmetry-breaking phenomenon. Nevertheless, seen from the deepest level of topology changes of equipotential submanifolds of phase space, the protein folding transition fully qualifies as a phase transition.

Physical systems that are dissipating, mixing, and developing turbulence also irreversibly transport statistical density. However, predicting the evolution of density from atomic and molecular scale dynamics is challenging for nonsteady, open, and driven nonequilibrium processes. Here, we establish a theory to address this challenge for classical dynamical systems that is analogous to the density matrix formulation of quantum mechanics. We show that a classical density matrix is similar to the phase-space metric and evolves in time according to generalizations of Liouville's theorem and Liouville's equation for non-Hamiltonian systems. The traditional Liouvillian forms are recovered in the absence of dissipation or driving by imposing trace preservation or by considering Hamiltonian dynamics. Local measures of dynamical instability and chaos are embedded in classical commutators and anticommutators and directly related to Poisson brackets when the dynamics are Hamiltonian. Because the classical density matrix is built from the Lyapunov vectors that underlie classical chaos, it offers an alternative computationally tractable basis for the statistical mechanics of nonequilibrium processes that applies to systems that are driven, transient, dissipative, regular, and chaotic.

When studying the collective motion of biological groups, a useful theoretical framework is that of ferromagnetic systems, in which the alignment interactions are a surrogate of the effective imitation among the individuals. In this context, the experimental discovery of scale-free correlations of speed fluctuations in starling flocks poses a challenge to common statistical physics wisdom, as in the ordered phase of standard ferromagnetic models with $O\left(n\right)$ symmetry, the modulus of the order parameter has finite correlation length. To make sense of this anomaly, a ferromagnetic theory has been proposed, where the bare confining potential has zero second derivative (i.e., it is marginal) along the modulus of the order parameter. The marginal model exhibits a zero-temperature critical point, where the modulus correlation length diverges, hence allowing us to boost both correlation and collective order by simply reducing the temperature. Here, we derive an effective field theory describing the marginal model close to the $T=0$ critical point and calculate the renormalization group equations at one loop within a momentum shell approach. We discover a nontrivial scenario, as the cubic and quartic vertices do not vanish in the infrared limit, while the coupling constants effectively regulating the exponents $\nu$ and $\eta$ have upper critical dimension $d_c=2$, so in three dimensions the critical exponents acquire their free values, $\nu =1/2$ and $\eta =0$. This theoretical scenario is verified by a Monte Carlo study of the modulus susceptibility in three dimensions, where the standard finite-size scaling relations have to be adapted to the case of $d>d_c$. The numerical data fully confirm our theoretical results.

Stochastic processes under resetting at random times have attracted a lot of attention in recent years and served as illustrations of nontrivial and interesting static and dynamic features of stochastic dynamics. In this paper, we aim to address how the entropy rate is affected by stochastic resetting in discrete-time Markovian processes, and we explore nontrivial effects of the resetting in the mixing properties of a stochastic process. In particular, we consider resetting random walks (RRWs) with a single resetting node on three different types of networks: degree-regular random networks, a finite-size Cayley tree, and a Barabási-Albert (BA) scale-free network, and we compute the entropy rate as a function of the resetting probability $\gamma$. Interestingly, for the first two types of networks, the entropy rate shows a nonmonotonic dependence on $\gamma$. There exists an optimal value of $\gamma$ at which the entropy rate reaches a maximum. Such a maximum is larger than that of maximal-entropy random walks (MREWs) and standard random walks (SRWs) on the same topology, while for the BA network the entropy rate of RRWs either shows a unique maximum or decreases monotonically with $\gamma$, depending upon the choice of the resetting node. When the maximum entropy rate of RRWs exists, it can be higher or lower than that of MREWs or SRWs. Our study reveals a nontrivial effect of stochastic resetting on nonequilibrium statistical physics.